On Sunday, January 8, 2017 at 7:53:37 PM UTC-8, Steven D'Aprano wrote:
> Suppose you have an expensive calculation that gets used two or more times in
> a
> loop. The obvious way to avoid calculating it twice in an ordinary loop is
> with
> a temporary variable:
>
> result = []
> for x in data:
> tmp = expensive_calculation(x)
> result.append((tmp, tmp+1))
>
>
> But what if you are using a list comprehension? Alas, list comps don't let
> you
> have temporary variables, so you have to write this:
>
>
> [(expensive_calculation(x), expensive_calculation(x) + 1) for x in data]
>
>
> Or do you? ... no, you don't!
>
>
> [(tmp, tmp + 1) for x in data for tmp in [expensive_calculation(x)]]
>
>
> I can't decide whether that's an awesome trick or a horrible hack...
>
>
> --
> Steven
> "Ever since I learned about confirmation bias, I've been seeing
> it everywhere." - Jon Ronson
Hello I saw some memoizing functions, in that sense you can use the
functools.lru_cache decorator, that is even better if you have repeated
elements in data.
@functools.lru_cache
def expensive_calculation(x):
# very NP-hard calculation
pass
Hope that helps :)
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